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All Journal Jurnal Pengabdian UntukMu NegeRI Unri Conference Series: Community Engagement Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Computer Science and Information Technology (CoSciTech) BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Indonesian Journal of Informatic Research and Software Engineering SATIN - Sains dan Teknologi Informasi BATOBO: Jurnal Pengabdian Kepada Masyarakat
-, Teguh Sujana
Teknik Informatika, STMIK Amik Riau
Religion Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Evaluasi Dosen Dibidang Pengajaran Menggunakan Metode Technique For Order Preference By Similarity To Ideal Solution (TOPSIS) (Studi Kasus : STMIK-AMIK Riau) Teguh Sujana -; Rahmiati -
SATIN - Sains dan Teknologi Informasi Vol 3 No 2 (2014): SATIN - Sains dan Teknologi Informasi
Publisher : STMIK Amik Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (839.431 KB) | DOI: 10.33372/stn.v3i2.361

Abstract

Salah satu penentu kualitas pendidikan tinggi adalah dosen. Dosen yang kompeten untuk melaksanakan tugasnya secara profesional adalah dosen yang memiliki kompetensi pedagogik, profesional, kepribadian dan sosial, sehingga perlu adanya penilaian yang mengacu kepada kompetensi dosen. Untuk mendapatkan hasil yang lebih sesuai dengan kualitas dosen maka penilaian yang dilakukan tidak hanya dari mahasiswa, tetapi juga dari teman sejawat, atasan, dan diri sendiri. Namun untuk memilih yang terbaik dari berbagai aspek penilaian menjadikan kendala dalam evaluasi dosen dibidang pengajaran. Metode Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) didasarkan pada konsep dimana alternatif terpilih yang terbaik tidak hanya memiliki jarak terpendek dari solusi ideal positif, namun juga memiliki jarak terpanjang dari solusi ideal negatif. Konsep ini banyak digunakan pada beberapa model MADM untuk menyelesaikan masalah keputusan secara praktis. Multiple Attribute Decision Making (MADM) digunakan untuk menyelesaikan masalah-masalah dalam ruang diskret. Oleh karena itu MADM biasanya digunakan untuk melakukan penilaian atau seleksi terhadap beberapa alternatif dalam jumlah yang terbatas. Hasil dari penelitian ini adalah dengan penggunaan metode TOPSIS dalam evaluasi dosen dibidang pengajaran dapat ditentukan dosen terbaik dibidang pengajaran yang berkompeten sehingga diharapkan dapat mendorong dosen untuk secara berkelanjutan meningkatkan profesionalismenya
Implementasi Machine Learning Untuk Prediksi Penyakit Jantung Menggunakan Algoritma Support Vector Machine Hidayat, Rahmat; Sy, Yandiko Saputra; Sujana, Teguh; Husnah, Mirdatul; Saputra, Haris Tri; Okmayura, Finanta
BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Vol 5 No 2 (2024): September
Publisher : Puslitbang Sinergis Asa Professional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37148/bios.v5i2.152

Abstract

Heart disease is currently a disease that has taken over many human lives. Data shows that more than 17 million people have died from heart disease. The high number of deaths, therefore, requires special handling to treat and prevent heart disease. In the development of technology, diagnosis of heart disease can be done with the help of information technology, one of which is through machine learning. This study aims to implement machine learning through the SVM algorithm to predict heart disease. The model formed by SVM produces an evaluation value indicated by an accuracy value of 0.85, a precision of 0.93, a recall of 0.76, and an f-1 score of 0.83. This model is used as training data to predict heart disease which is then successfully used to create a system through the Streamlit library which can be easily accessed via the website.
Perbandingan Metode Learning Vector Quantization Dan Backpropagation Dalam Klasifikasi Personality Pada Anak Novita, Rita; Sujana, Teguh; Agusviyanda, Agusviyanda; Fitri, Triyani Arita; Susanti, Susanti
Computer Science and Information Technology Vol 5 No 3 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This research focuses on classifying children's personalities at Rumah Bermain Bilal using Artificial Neural Network algorithms, specifically Learning Vector Quantization (LVQ) and Backpropagation. The primary objective of this study is to evaluate the effectiveness of these algorithms in categorizing children's personality data and to identify the most accurate method for educational settings. The experiments were conducted with various configurations, including the number of iterations and learning rate, to assess the performance of each algorithm comprehensively. The findings show that the LVQ method demonstrates higher accuracy than Backpropagation. For training data, LVQ achieved an accuracy of 73.47%, whereas Backpropagation reached only 40.82%. For test data, LVQ achieved an accuracy of 84.62%, significantly outperforming Backpropagation's 53.85%. These results indicate that LVQ is more effective in personality classification, especially in an educational context. It is hoped that these findings will assist educational institutions in implementing artificial intelligence-based methods to understand children's personality traits better, thereby supporting the development of more targeted teaching strategies.
Pelatihan Membuat Label Kemasan Produk Pelaku UMKM Kecamatan Bandar Laksamana Kabupaten Bengkalis Menggunakan Canva Salambue, Roni; Risanto, Joko; Fitriansyah, Aidil; Sukamto, Sukamto; Bahri, Zaiful; Mahdiyah, Evfi; Hidayat, Rahmat; Sujana, Teguh; Sy, Yandiko Saputra
Unri Conference Series: Community Engagement Vol 6 (2024): Seminar Nasional Pemberdayaan Masyarakat
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/unricsce.6.364-369

Abstract

Micro, Small and Medium Enterprises (UMKM) in Bandar Laksamana District, Bengkalis, Riau have been identified by FMIPA students from Riau University who participated in the Belajar Kampus Merdeka (MBKM) Community Service Program (Kukerta) in 2024. There are 66 UMKM in three villages with various businesses such as stalls, fried foods, beauty, culinary, craftsmen. The people of one village seemed apathetic in managing UMKM because they were considered as side businesses only, had no prospects for development and were not interested in participating in online marketing training. From observations, several UMKM products have the potential to be marketed online because they are unique as typical Malay foods. An approach was made to UMKM actors to be assisted in having the skills to design attractive and dynamic packaging labels, assisting online marketing until the market reaches various corners of the country. A good product packaging label will advance the business and introduce the diversity of typical Malay culinary delights to the public. Canva is a simple graphic design application that is easy for beginners to use. Canva provides paid and free services with various easy-to-adopt template features with various completeness such as image cropping, text insertion, color, and so on. The Canva application needs to be introduced to UMKM to attract their product market through unique and attractive banner, poster, and banner designs so that the product display remains fresh, updated according to needs.
Penerapan Pembelajaran Berbasis Proyek Menggunakan Internet of Things (IoT) pada Pembuatan Tong Sampah Otomatis di SMK Negeri 1 Tuah Kemuning, Indragiri Hilir Tri Saputra, Haris; Suri Tauladan, Imam; Apriwandi; Sujana, Teguh; Rifqi Harimardika, Musyaffa; Gemala Jondya, Aisha; Firdaus
BATOBO: Jurnal Pengabdian Kepada Masyarakat Vol 3 No 1: BATOBO: Juni 2025
Publisher : Jurusan Teknik Elektro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/batobo.3.1.120-128

Abstract

Kesenjangan antara kurikulum pembelajaran dan kebutuhan teknologi industri semakin nyata dalam Pendidikan Tingkat Menengah Kejuruan (SMK), khususnya terkait belum diterapkannya teknologi Internet of Things (IoT) dalam proses pembelajaran. Kondisi ini mendorong perlunya penguatan keterampilan berbasis teknologi terkini bagi siswa melalui kegiatan nyata yang relevan. Kegiatan Pengabdian kepada Masyarakat (PkM) ini bertujuan untuk mengimplementasikan teknologi IoT melalui pembuatan tong sampah otomatis pada SMK Negeri 1 Tuah Kemuning Indragiri Hilir. Selain peningkatan kesadaran pengelolaan sampah, kegiatan PkM ini merupakan solusi inovatif terhadap penguatan keterampilan berbasis teknologi terkini. Kegiatan PkM ini dilaksanakan dengan menggunakan metode pembelajaran berbasis proyek yang melalui tiga tahapan utama yaitu Perencanaan Kegiatan Mitra, Pelatihan Teknis dan Perakitan, Pengujian Fungsional dan Refleksi Hasil. Dalam tahapan pelatihan dan implementasi, awal kegiatan dimulai dengan memberikan penjelasan konsep dasar IoT kepada guru dan siswa. Selanjutnya,  kegiatan desain dan pembuatan rancang bangun tong sampah otomatis yang dilengkapi dengan sensor mendeteksi volume sampah. Tong sampah otomatis juga dilengkapi dengan sistem notifikasi berbasis aplikasi mobile dengan tujuan memudahkan pengelolaan sampah secara efisien. Selain itu, implementasi IoT dalam pengelolaan sampah bertujuan untuk memperkenalkan konsep smart city yang ramah lingkungan dan mengedukasi generasi muda tentang pentingnya pengelolaan sampah berbasis teknologi. Hasil dari kegiatan PkM ini menunjukkan bahwa penerapan teknologi IoT dapat memberikan konstribusi positif terhadap peningkatan kualitas lingkungan sekolah serta meningkatkan dan keterampilan siswa dalam bidang teknologi. Dari hasil pengukuran kuantitatif dapat disimpulkan bahwa, sebesar 96,67% mahasiswa berhasil memahami penerapan konsep teknologi IoT.
Implementasi Learning Vector Quantization (LVQ) Untuk Klasifikasi Gaya Belajar Sujana, Teguh; Novita, Rita; Tri Saputra, Haris; Agusviyanda
JURNAL FASILKOM Vol. 15 No. 1 (2025): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v15i1.8952

Abstract

Gaya belajar merupakan preferensi individu dalam memperoleh, memproses, dan memahami informasi baru, yang secara umum dikelompokkan menjadi tiga kategori utama: visual, auditori, dan kinestetik. Penelitian ini bertujuan untuk mengembangkan metode klasifikasi otomatis guna mengidentifikasi gaya belajar siswa secara efisien. Algoritma Learning Vector Quantization (LVQ) digunakan untuk mengklasifikasikan gaya belajar berdasarkan 100 sampel data, dengan struktur jaringan yang terdiri dari 36 neuron pada lapisan input dan 3 neuron pada lapisan output. Implementasi dilakukan menggunakan perangkat lunak MATLAB, dan model dievaluasi menggunakan metrik akurasi serta Mean Square Error (MSE). Pengujian dilakukan dengan berbagai rasio data latih dan data uji, dan konfigurasi terbaik diperoleh saat menggunakan 90 data sebagai data latih dan 10 data sebagai data uji, dengan learning rate sebesar 0.05 dan iterasi sebanyak 500. Hasil menunjukkan akurasi mencapai 80% dan nilai MSE minimum sebesar 0.12. Temuan ini menunjukkan bahwa penambahan jumlah data latih berdampak positif terhadap akurasi model. Penelitian ini memberikan kontribusi dalam pengembangan sistem klasifikasi gaya belajar otomatis yang dapat diintegrasikan ke dalam sistem pendidikan untuk mendukung strategi pembelajaran yang lebih personal dan adaptif secara efektif.
Design of Artificial Immune System - Models and Algorithms: Design of Artificial Immune System - Models and Algorithms Sujana, Teguh; Nas, Chairun
Indonesian Journal of Informatic Research and Software Engineering (IJIRSE) Vol. 5 No. 2 (2025): Indonesian Journal of Informatic Research and Software Engineering (IJIRSE)
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/ijirse.v5i2.2246

Abstract

Artificial Immune Systems (AIS) belong to a group of computational intelligence methods inspired by the working mechanisms of biological immune systems to solve various computational problems. Artificial Neural Networks (ANNs) themselves are often used in various fields such as anomaly detection, pattern recognition, cyber and network security, task scheduling, process optimization, and data analysis, with the application of various ANN algorithms. In the AIS approach, there are four basic algorithms that serve as the main foundation, namely the Negative Selection Algorithm (NSA), Artificial Immune Networks (aiNet), Clonal Selection Algorithm (CLONALG), and Dendritic Cell Algorithm (DCA). The problem that occurs at this time is that there is still a lack of papers that discuss the main basic algorithms in AIS, resulting in difficulties in developing new models of basic algorithms. Apart from that, many other aspects of the natural immune system have not been touched due to not yet understanding the basic algorithm of AIS. This paper aims to explain the main models and algorithms in AIS above so that in future research, new algorithms can be developed based on the basic algorithm as a reference. The results of this paper are a review of the main basic models and algorithms in AIS.
Enhancing Teachers' Knowledge of Artificial Intelligence and Information Technology at SMPN 11 Pekanbaru: Penguatan Literasi Teknologi Informasi dan Artificial Intelligence bagi Pendidik SMPN 11 Pekanbaru Sujana, Teguh; Amalia Putri, Rizka; Nasfianti, Iis; Wulandari, Nindya; Fawrin, Heralda
Jurnal Pengabdian UntukMu NegeRI Vol. 9 No. 3 (2025): Pengabdian Untuk Mu negeRI
Publisher : LPPM UMRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jpumri.v9i3.10349

Abstract

Rapid technological advancements necessitate that educators constantly adjust to new advances, such as the application of artificial intelligence (AI) and information technology in the classroom. The fact remains that many educators are still not accustomed to incorporating technology into their lessons. By promoting the use of AI as a learning aid and adopting IT-based learning, this community service project seeks to improve the knowledge and abilities of SMPN 11 Pekanbaru instructors. The Participatory Rural Appraisal (PRA) method was used in the activity, which was conducted as a workshop with materials, discussions, and practical application. A variety of applications that can aid in the learning process were presented to the teachers. The activity's outcomes demonstrated a rise in teachers' technological knowledge and proficiency as well as the appearance of motivation to innovate in the classroom. Teachers can better prepare for the difficulties of teaching in the digital age by starting with this activity.
Co-Authors Agusviyanda Agusviyanda Agusviyanda Amalia Putri, Rizka Apriwandi Fawrin, Heralda Finanta Okmayura Firdaus Fitriansyah, Aidil Gemala Jondya, Aisha Husnah, Mirdatul Imam Suri Tauladan Mahdiyah, Evfi MUSYAFFA RIFQI HARIMARDIKA Nas, Chairun Nasfianti, Iis Rahmat Hidayat Rahmiati Rahmiati -, Rahmiati Risanto, Joko Rita Novita Rita Novita Roni Salambue Saputra, Haris Tri Sukamto Sukamto Susanti Susanti Sy, Yandiko Saputra Triyani Arita Fitri Zaiful Bahri